Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

Growth rates

Heat maps

  • The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
  • The first plot compares growth rate for total cases; the second, growth rate for total deaths.
  • The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
  • The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
    • You can use the plots to track each geography over time and to compare the geographies to one another.
    • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

  • This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
    • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
    • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

  • This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
    • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
    • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

  • This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
  • For each metric, in addition to the tables, the trends for the top states are plotted over time.
    • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)
Ranking State Cases Per Million
1 North Dakota 122,694
2 South Dakota 114,254
3 Iowa 91,376
4 Wisconsin 91,351
5 Utah 90,129
6 Rhode Island 88,593
7 Nebraska 88,551
8 Tennessee 88,209
9 Idaho 81,213
10 Kansas 80,561
11 Indiana 79,629
12 Arkansas 79,159
13 Wyoming 78,735
14 Arizona 78,540
15 Illinois 78,482
16 Montana 78,153
17 Oklahoma 77,905
18 Alabama 77,417
19 Nevada 76,529
20 Mississippi 75,750
21 Minnesota 75,416
22 New Mexico 70,820
23 Missouri 70,523
24 Louisiana 70,265
25 Alaska 66,027
26 Florida 64,816
27 Georgia 64,304
28 Texas 64,291
29 South Carolina 63,719
30 Kentucky 63,689
31 California 63,570
32 Ohio 62,879
33 Delaware 62,746
34 Colorado 60,513
35 Massachusetts 57,628
36 New Jersey 56,478
37 Connecticut 55,246
38 North Carolina 55,139
39 Michigan 54,557
40 New York 53,899
41 Pennsylvania 53,097
42 West Virginia 51,983
43 Maryland 47,956
44 Virginia 43,572
45 District of Columbia 42,743
46 Puerto Rico 35,361
47 New Hampshire 35,295
48 Washington 34,631
49 Oregon 28,334
50 Maine 19,762
51 Hawaii 15,678
52 Vermont 12,881

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)
Ranking State New Cases Per Million
1 Rhode Island 1,857
2 Arizona 1,488
3 Oklahoma 1,028
4 South Carolina 994
5 California 960
6 Arkansas 822
7 Louisiana 815
8 Texas 808
9 Delaware 762
10 Utah 749
11 West Virginia 713
12 Alabama 689
13 New Hampshire 688
14 Nevada 662
15 Kentucky 652
16 Georgia 648
17 Connecticut 640
18 Tennessee 634
19 Massachusetts 629
20 New York 627
21 North Carolina 583
22 Ohio 579
23 Florida 578
24 Mississippi 578
25 Wyoming 573
26 Idaho 530
27 Virginia 513
28 Kansas 497
29 Indiana 496
30 New Mexico 495
31 Missouri 485
32 Montana 479
33 Wisconsin 471
34 Nebraska 470
35 Pennsylvania 469
36 South Dakota 469
37 Iowa 465
38 Colorado 464
39 Washington 456
40 Illinois 442
41 Minnesota 439
42 New Jersey 422
43 Maryland 363
44 Alaska 343
45 Maine 327
46 District of Columbia 310
47 Michigan 301
48 North Dakota 263
49 Oregon 249
50 Vermont 186
51 Puerto Rico 144
52 Hawaii 71

Total deaths

Table of total deaths per million residents (all 50 states)
Ranking State Deaths Per Million
1 New Jersey 2,182
2 New York 1,969
3 Massachusetts 1,847
4 Rhode Island 1,765
5 North Dakota 1,753
6 Connecticut 1,736
7 South Dakota 1,710
8 Mississippi 1,671
9 Louisiana 1,642
10 Illinois 1,465
11 Michigan 1,361
12 Pennsylvania 1,295
13 Indiana 1,286
14 Arizona 1,285
15 Arkansas 1,271
16 Iowa 1,267
17 New Mexico 1,238
18 District of Columbia 1,134
19 South Carolina 1,067
20 Tennessee 1,054
21 Nevada 1,053
22 Florida 1,033
23 Georgia 1,010
24 Maryland 1,006
25 Texas 998
26 Missouri 997
27 Alabama 996
28 Kansas 994
29 Minnesota 978
30 Delaware 972
31 Montana 941
32 Wisconsin 922
33 Nebraska 896
34 Colorado 878
35 Idaho 824
36 West Virginia 804
37 Wyoming 801
38 Ohio 791
39 California 695
40 Kentucky 692
41 North Carolina 675
42 Oklahoma 649
43 Virginia 608
44 New Hampshire 582
45 Puerto Rico 489
46 Washington 474
47 Utah 409
48 Oregon 367
49 Alaska 285
50 Maine 274
51 Vermont 238
52 Hawaii 202

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)
Ranking State New Deaths Per Million
1 Rhode Island 29
2 Mississippi 15
3 Tennessee 14
4 Wyoming 14
5 Arizona 13
6 Indiana 12
7 West Virginia 12
8 Arkansas 11
9 Massachusetts 11
10 Missouri 11
11 Louisiana 10
12 Michigan 10
13 Montana 10
14 Illinois 9
15 Nevada 9
16 New Mexico 9
17 Connecticut 8
18 North Dakota 8
19 Pennsylvania 8
20 California 7
21 Kentucky 7
22 New Jersey 7
23 New York 7
24 South Carolina 7
25 Maryland 6
26 Nebraska 6
27 Ohio 6
28 Wisconsin 6
29 Delaware 5
30 Iowa 5
31 New Hampshire 5
32 Texas 5
33 Vermont 5
34 Colorado 4
35 District of Columbia 4
36 Florida 4
37 Idaho 4
38 Minnesota 4
39 North Carolina 4
40 South Dakota 4
41 Georgia 3
42 Oklahoma 3
43 Oregon 3
44 Puerto Rico 3
45 Washington 3
46 Kansas 2
47 Maine 2
48 Utah 2
49 Virginia 2
50 Alabama 0
51 Alaska 0
52 Hawaii 0

Counties

  • This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
    • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
  • In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Cases Per Million Raw Ranking Percentile
Crowley Colorado 274,872 1 99
Dewey South Dakota 221,656 2 99
Norton Kansas 221,227 3 99
Lincoln Arkansas 218,980 4 99
Bon Homme South Dakota 214,751 5 99
Davidson Tennessee 103,633 292 90
Richland South Carolina 66,308 1609 48
York South Carolina 58,495 1996 36
Orange California 57,263 2051 34
Pierce Washington 31,965 2840 9

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Deaths Per Million Raw Ranking Percentile
Gove Kansas 8,346 1 99
Jerauld South Dakota 7,452 2 99
Dickey North Dakota 6,568 3 99
Gregory South Dakota 6,213 4 99
Iron Wisconsin 6,154 5 99
Davidson Tennessee 864 1802 42
Richland South Carolina 827 1863 40
York South Carolina 669 2133 32
Orange California 606 2241 28
Pierce Washington 404 2591 17

Our county percentiles over time

Raw counts

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons